Graduate Thesis Or Dissertation
 

Biochemical conversion of lignocellulosic biomass to ethanol : experimental, enzymatic hydrolysis modeling, techno-economic and life cycle assessment studies

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  • Ethanol production from lignocellulosic feedstock has been under intense scrutiny as a transportation fuel due to its potential to address concerns of increasing energy consumption, limited fossil energy resources, climate changes due to greenhouse gas emissions from fossil fuels, and especially use of non-food biomaterials, which address the biggest limitation of first generation bioethanol. Despite these advantages, the lignocellulosic ethanol production on commercial scale is still on verge because of high processing costs of ethanol production. In the biochemical conversion process, biomass is converted to ethanol by sequential steps of pretreatment (to reduce the recalcitrance of biomass), hydrolysis (conversion of sugar polymers to monomers) and fermentation (sugars to ethanol). Every year, about a million ton of grass straw is available as agricultural residue in Pacific Northwest. There were no previous comprehensive studies to evaluate the technical feasibility, economic viability and environmental sustainability of the bioethanol produced using grass straw in Willamette valley. The focus of this dissertation was to investigate the potential of cellulosic ethanol production from grass straw, assess the techno-economic viability and environmental impacts of the bioethanol production and development of a stochastic molecular model for modeling cellulose hydrolysis. This dissertation was divided into four studies focused on individual aspects of the overall objective. The first study evaluated the ethanol production potential from straws produced from three major grass seed varieties (perennial ryegrass (Lolium perenne L.), tall fescue (Festuca arundinacea Schreb) and bentgrass (Agrostis sp.)) in Pacific Northwest. Feedstocks were pretreated using three chemical pretreatments (dilute acid, dilute alkali, and hot water) and subsequently hydrolyzed enzymatically to investigate the effect of pretreatment and estimate the potential ethanol yields. Carbohydrate content in biomass varied from 40.6 to 52.9%, with tall fescue having the maximum cellulose content of 32.4%. All pretreatment were effective in increasing the hydrolysis yields, and theoretical maximum ethanol yields were in the range of 276 to 360 L per ton of biomass. The second study performed the comprehensive techno-economic analysis of ethanol production from tall fescue using dilute acid, dilute alkali, hot water, and steam explosion pretreatment technologies. Detailed process models incorporating all unit operations in lignocellulosic ethanol plant with 250,000 metric ton biomass/ year processing capacity were developed in SuperPro Designer. The ethanol production cost were estimated from $0.81 to $0.88/ L of ethanol, and were found highly sensitive to biomass price, enzyme cost, and pentose sugar fermentation efficiency. Energy from lignin residue burning was found sufficient to meet the steam requirement in the production process. Third study performed the life cycle assessment for bioethanol production from grass straw considering various pretreatment technology options. The study revealed that ethanol production from grass straw provide environmental benefits compared to use of gasoline, with 57.43–112.67% reduction in fossil energy use to produce 10,000 MJ of fuel. The GHG emissions during life cycle of ethanol production were estimated in the range of -131 to −555.4 kg CO2 eq. per 10,000 MJ of fuel. It was observed that assumptions and allocation procedure used during the analysis had a significant effect on the LCA results. During the techno-economic assessment of bioethanol process, it was found that cost of cellulose enzymes was significant fraction of the total ethanol production cost. A comprehensive enzymatic hydrolysis model can play critical role in optimizing the enzyme composition and dosage, improving understanding of the process mechanism and reducing the cost of enzymes, a major bottleneck in the ethanol production process. A novel approach of stochastic molecular modeling, in which each hydrolysis event is translated into a discrete event, was used to develop a mechanistic model for cellulose hydrolysis in the fourth study. Cellulose structure was modeled as a group of microfibrils consisting of elementary fibrils bundles, where each elementary fibril was represented as a three dimensional matrix of glucose molecules. Major structural properties: crystallinity, degree of polymerization, surface accessibility, and enzyme characteristics: mode of action, binding and surface blockage, inhibition, along with the dynamic morphological changes in structure of cellulose were incorporated in the model. Hydrolysis of cellulose was simulated based on Monte Carlo simulation technique. Hydrolysis results predicted by model simulations had shown a good fit with the experimental data from hydrolysis of pure cellulose using purified enzymes for various hydrolysis conditions. The model was effective in capturing the dynamic behavior of cellulose hydrolysis during action of individual as well as multiple cellulases. Model was able to simulate and validate all the important expected experimental observations: effect of structural properties, enzyme inhibition and enzyme loadings on the hydrolysis and degree of synergism on different substrates. The work from this dissertation proved the significance of choosing technology options, drew a comparison among different pretreatment technologies, identified the critical processes and inputs that have significant effect on the ethanol production cost, net energy, and GHG emissions. Results from the last study confirmed the validity of using the stochastic molecular modeling approach to quantitatively and qualitatively describe the cellulose hydrolysis, which has wide potential application in bioethanol production research to reduce the enzyme cost.
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